{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#根据美国农业部数据，得到每种食物的营养成分和分量数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "db = json.load(open('./usda_food.json'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6636"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(db)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['id', 'description', 'tags', 'manufacturer', 'group', 'portions', 'nutrients'])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "db[0].keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'description': 'Protein',\n",
       " 'group': 'Composition',\n",
       " 'units': 'g',\n",
       " 'value': 25.18}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "db[0]['nutrients'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 389355 entries, 0 to 389354\n",
      "Data columns (total 5 columns):\n",
      "description    389355 non-null object\n",
      "group          389355 non-null object\n",
      "units          389355 non-null object\n",
      "value          389355 non-null float64\n",
      "id             389355 non-null int64\n",
      "dtypes: float64(1), int64(1), object(3)\n",
      "memory usage: 14.9+ MB\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "nutrients_list = []\n",
    "for item in db:\n",
    "    nutrients = pd.DataFrame(item['nutrients'])\n",
    "    nutrients['id'] = item['id']\n",
    "    nutrients_list.append(nutrients)\n",
    "nutrients = pd.concat(nutrients_list, ignore_index=True)\n",
    "nutrients.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>description</th>\n",
       "      <th>group</th>\n",
       "      <th>units</th>\n",
       "      <th>value</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>389350</th>\n",
       "      <td>Vitamin B-12, added</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389351</th>\n",
       "      <td>Cholesterol</td>\n",
       "      <td>Other</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389352</th>\n",
       "      <td>Fatty acids, total saturated</td>\n",
       "      <td>Other</td>\n",
       "      <td>g</td>\n",
       "      <td>0.072</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389353</th>\n",
       "      <td>Fatty acids, total monounsaturated</td>\n",
       "      <td>Other</td>\n",
       "      <td>g</td>\n",
       "      <td>0.028</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389354</th>\n",
       "      <td>Fatty acids, total polyunsaturated</td>\n",
       "      <td>Other</td>\n",
       "      <td>g</td>\n",
       "      <td>0.041</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               description     group units  value     id\n",
       "389350                 Vitamin B-12, added  Vitamins   mcg  0.000  43546\n",
       "389351                         Cholesterol     Other    mg  0.000  43546\n",
       "389352        Fatty acids, total saturated     Other     g  0.072  43546\n",
       "389353  Fatty acids, total monounsaturated     Other     g  0.028  43546\n",
       "389354  Fatty acids, total polyunsaturated     Other     g  0.041  43546"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nutrients.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#提取食物的名称、分类、编号、制造商等信息\n",
    "info_keys = ['description', 'group', 'id', 'manufacturer']\n",
    "info = pd.DataFrame(db, columns=info_keys)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>description</th>\n",
       "      <th>group</th>\n",
       "      <th>id</th>\n",
       "      <th>manufacturer</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6631</th>\n",
       "      <td>Bologna, beef, low fat</td>\n",
       "      <td>Sausages and Luncheon Meats</td>\n",
       "      <td>42161</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6632</th>\n",
       "      <td>Turkey and pork sausage, fresh, bulk, patty or...</td>\n",
       "      <td>Sausages and Luncheon Meats</td>\n",
       "      <td>42173</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6633</th>\n",
       "      <td>Babyfood, juice, pear</td>\n",
       "      <td>Baby Foods</td>\n",
       "      <td>43408</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6634</th>\n",
       "      <td>Babyfood, dessert, banana yogurt, strained</td>\n",
       "      <td>Baby Foods</td>\n",
       "      <td>43539</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6635</th>\n",
       "      <td>Babyfood, banana no tapioca, strained</td>\n",
       "      <td>Baby Foods</td>\n",
       "      <td>43546</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            description  \\\n",
       "6631                             Bologna, beef, low fat   \n",
       "6632  Turkey and pork sausage, fresh, bulk, patty or...   \n",
       "6633                              Babyfood, juice, pear   \n",
       "6634         Babyfood, dessert, banana yogurt, strained   \n",
       "6635              Babyfood, banana no tapioca, strained   \n",
       "\n",
       "                            group     id manufacturer  \n",
       "6631  Sausages and Luncheon Meats  42161               \n",
       "6632  Sausages and Luncheon Meats  42173               \n",
       "6633                   Baby Foods  43408         None  \n",
       "6634                   Baby Foods  43539         None  \n",
       "6635                   Baby Foods  43546         None  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "info.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6636 entries, 0 to 6635\n",
      "Data columns (total 4 columns):\n",
      "description     6636 non-null object\n",
      "group           6636 non-null object\n",
      "id              6636 non-null int64\n",
      "manufacturer    5195 non-null object\n",
      "dtypes: int64(1), object(3)\n",
      "memory usage: 207.5+ KB\n"
     ]
    }
   ],
   "source": [
    "info.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Vegetables and Vegetable Products    812\n",
       "Beef Products                        618\n",
       "Baked Products                       496\n",
       "Breakfast Cereals                    403\n",
       "Fast Foods                           365\n",
       "Legumes and Legume Products          365\n",
       "Lamb, Veal, and Game Products        345\n",
       "Sweets                               341\n",
       "Fruits and Fruit Juices              328\n",
       "Pork Products                        328\n",
       "Name: group, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.value_counts(info.group)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>description</th>\n",
       "      <th>group</th>\n",
       "      <th>units</th>\n",
       "      <th>value</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Protein</td>\n",
       "      <td>Composition</td>\n",
       "      <td>g</td>\n",
       "      <td>25.180</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Total lipid (fat)</td>\n",
       "      <td>Composition</td>\n",
       "      <td>g</td>\n",
       "      <td>29.200</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Carbohydrate, by difference</td>\n",
       "      <td>Composition</td>\n",
       "      <td>g</td>\n",
       "      <td>3.060</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ash</td>\n",
       "      <td>Other</td>\n",
       "      <td>g</td>\n",
       "      <td>3.280</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Energy</td>\n",
       "      <td>Energy</td>\n",
       "      <td>kcal</td>\n",
       "      <td>376.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Water</td>\n",
       "      <td>Composition</td>\n",
       "      <td>g</td>\n",
       "      <td>39.280</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Energy</td>\n",
       "      <td>Energy</td>\n",
       "      <td>kJ</td>\n",
       "      <td>1573.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Fiber, total dietary</td>\n",
       "      <td>Composition</td>\n",
       "      <td>g</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Calcium, Ca</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mg</td>\n",
       "      <td>673.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Iron, Fe</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.640</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Magnesium, Mg</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mg</td>\n",
       "      <td>22.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Phosphorus, P</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mg</td>\n",
       "      <td>490.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Potassium, K</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mg</td>\n",
       "      <td>93.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Sodium, Na</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mg</td>\n",
       "      <td>690.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Zinc, Zn</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mg</td>\n",
       "      <td>2.940</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Copper, Cu</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.024</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Manganese, Mn</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.021</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Selenium, Se</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mcg</td>\n",
       "      <td>14.500</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Vitamin A, IU</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>IU</td>\n",
       "      <td>1054.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Retinol</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>262.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Vitamin A, RAE</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg_RAE</td>\n",
       "      <td>271.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Vitamin C, total ascorbic acid</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Thiamin</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.031</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Riboflavin</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.450</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Niacin</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.180</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Pantothenic acid</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.190</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Vitamin B-6</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.074</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Folate, total</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>18.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Vitamin B-12</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>0.270</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Folic acid</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389325</th>\n",
       "      <td>Selenium, Se</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mcg</td>\n",
       "      <td>1.100</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389326</th>\n",
       "      <td>Vitamin A, IU</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>IU</td>\n",
       "      <td>5.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389327</th>\n",
       "      <td>Retinol</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389328</th>\n",
       "      <td>Vitamin A, RAE</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg_RAE</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389329</th>\n",
       "      <td>Carotene, beta</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>2.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389330</th>\n",
       "      <td>Carotene, alpha</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>2.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389331</th>\n",
       "      <td>Vitamin E (alpha-tocopherol)</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.250</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389332</th>\n",
       "      <td>Vitamin D</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>IU</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389333</th>\n",
       "      <td>Vitamin D (D2 + D3)</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389334</th>\n",
       "      <td>Cryptoxanthin, beta</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389335</th>\n",
       "      <td>Lycopene</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389336</th>\n",
       "      <td>Lutein + zeaxanthin</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>20.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389337</th>\n",
       "      <td>Vitamin C, total ascorbic acid</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>21.900</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389338</th>\n",
       "      <td>Thiamin</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.020</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389339</th>\n",
       "      <td>Riboflavin</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.060</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389340</th>\n",
       "      <td>Niacin</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.540</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389341</th>\n",
       "      <td>Vitamin B-6</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.260</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389342</th>\n",
       "      <td>Folate, total</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>17.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389343</th>\n",
       "      <td>Vitamin B-12</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389344</th>\n",
       "      <td>Choline, total</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>4.100</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389345</th>\n",
       "      <td>Vitamin K (phylloquinone)</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>0.500</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389346</th>\n",
       "      <td>Folic acid</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389347</th>\n",
       "      <td>Folate, food</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>17.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389348</th>\n",
       "      <td>Folate, DFE</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg_DFE</td>\n",
       "      <td>17.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389349</th>\n",
       "      <td>Vitamin E, added</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389350</th>\n",
       "      <td>Vitamin B-12, added</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389351</th>\n",
       "      <td>Cholesterol</td>\n",
       "      <td>Other</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389352</th>\n",
       "      <td>Fatty acids, total saturated</td>\n",
       "      <td>Other</td>\n",
       "      <td>g</td>\n",
       "      <td>0.072</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389353</th>\n",
       "      <td>Fatty acids, total monounsaturated</td>\n",
       "      <td>Other</td>\n",
       "      <td>g</td>\n",
       "      <td>0.028</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389354</th>\n",
       "      <td>Fatty acids, total polyunsaturated</td>\n",
       "      <td>Other</td>\n",
       "      <td>g</td>\n",
       "      <td>0.041</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>389355 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               description        group    units     value  \\\n",
       "0                                  Protein  Composition        g    25.180   \n",
       "1                        Total lipid (fat)  Composition        g    29.200   \n",
       "2              Carbohydrate, by difference  Composition        g     3.060   \n",
       "3                                      Ash        Other        g     3.280   \n",
       "4                                   Energy       Energy     kcal   376.000   \n",
       "5                                    Water  Composition        g    39.280   \n",
       "6                                   Energy       Energy       kJ  1573.000   \n",
       "7                     Fiber, total dietary  Composition        g     0.000   \n",
       "8                              Calcium, Ca     Elements       mg   673.000   \n",
       "9                                 Iron, Fe     Elements       mg     0.640   \n",
       "10                           Magnesium, Mg     Elements       mg    22.000   \n",
       "11                           Phosphorus, P     Elements       mg   490.000   \n",
       "12                            Potassium, K     Elements       mg    93.000   \n",
       "13                              Sodium, Na     Elements       mg   690.000   \n",
       "14                                Zinc, Zn     Elements       mg     2.940   \n",
       "15                              Copper, Cu     Elements       mg     0.024   \n",
       "16                           Manganese, Mn     Elements       mg     0.021   \n",
       "17                            Selenium, Se     Elements      mcg    14.500   \n",
       "18                           Vitamin A, IU     Vitamins       IU  1054.000   \n",
       "19                                 Retinol     Vitamins      mcg   262.000   \n",
       "20                          Vitamin A, RAE     Vitamins  mcg_RAE   271.000   \n",
       "21          Vitamin C, total ascorbic acid     Vitamins       mg     0.000   \n",
       "22                                 Thiamin     Vitamins       mg     0.031   \n",
       "23                              Riboflavin     Vitamins       mg     0.450   \n",
       "24                                  Niacin     Vitamins       mg     0.180   \n",
       "25                        Pantothenic acid     Vitamins       mg     0.190   \n",
       "26                             Vitamin B-6     Vitamins       mg     0.074   \n",
       "27                           Folate, total     Vitamins      mcg    18.000   \n",
       "28                            Vitamin B-12     Vitamins      mcg     0.270   \n",
       "29                              Folic acid     Vitamins      mcg     0.000   \n",
       "...                                    ...          ...      ...       ...   \n",
       "389325                        Selenium, Se     Elements      mcg     1.100   \n",
       "389326                       Vitamin A, IU     Vitamins       IU     5.000   \n",
       "389327                             Retinol     Vitamins      mcg     0.000   \n",
       "389328                      Vitamin A, RAE     Vitamins  mcg_RAE     0.000   \n",
       "389329                      Carotene, beta     Vitamins      mcg     2.000   \n",
       "389330                     Carotene, alpha     Vitamins      mcg     2.000   \n",
       "389331        Vitamin E (alpha-tocopherol)     Vitamins       mg     0.250   \n",
       "389332                           Vitamin D     Vitamins       IU     0.000   \n",
       "389333                 Vitamin D (D2 + D3)     Vitamins      mcg     0.000   \n",
       "389334                 Cryptoxanthin, beta     Vitamins      mcg     0.000   \n",
       "389335                            Lycopene     Vitamins      mcg     0.000   \n",
       "389336                 Lutein + zeaxanthin     Vitamins      mcg    20.000   \n",
       "389337      Vitamin C, total ascorbic acid     Vitamins       mg    21.900   \n",
       "389338                             Thiamin     Vitamins       mg     0.020   \n",
       "389339                          Riboflavin     Vitamins       mg     0.060   \n",
       "389340                              Niacin     Vitamins       mg     0.540   \n",
       "389341                         Vitamin B-6     Vitamins       mg     0.260   \n",
       "389342                       Folate, total     Vitamins      mcg    17.000   \n",
       "389343                        Vitamin B-12     Vitamins      mcg     0.000   \n",
       "389344                      Choline, total     Vitamins       mg     4.100   \n",
       "389345           Vitamin K (phylloquinone)     Vitamins      mcg     0.500   \n",
       "389346                          Folic acid     Vitamins      mcg     0.000   \n",
       "389347                        Folate, food     Vitamins      mcg    17.000   \n",
       "389348                         Folate, DFE     Vitamins  mcg_DFE    17.000   \n",
       "389349                    Vitamin E, added     Vitamins       mg     0.000   \n",
       "389350                 Vitamin B-12, added     Vitamins      mcg     0.000   \n",
       "389351                         Cholesterol        Other       mg     0.000   \n",
       "389352        Fatty acids, total saturated        Other        g     0.072   \n",
       "389353  Fatty acids, total monounsaturated        Other        g     0.028   \n",
       "389354  Fatty acids, total polyunsaturated        Other        g     0.041   \n",
       "\n",
       "           id  \n",
       "0        1008  \n",
       "1        1008  \n",
       "2        1008  \n",
       "3        1008  \n",
       "4        1008  \n",
       "5        1008  \n",
       "6        1008  \n",
       "7        1008  \n",
       "8        1008  \n",
       "9        1008  \n",
       "10       1008  \n",
       "11       1008  \n",
       "12       1008  \n",
       "13       1008  \n",
       "14       1008  \n",
       "15       1008  \n",
       "16       1008  \n",
       "17       1008  \n",
       "18       1008  \n",
       "19       1008  \n",
       "20       1008  \n",
       "21       1008  \n",
       "22       1008  \n",
       "23       1008  \n",
       "24       1008  \n",
       "25       1008  \n",
       "26       1008  \n",
       "27       1008  \n",
       "28       1008  \n",
       "29       1008  \n",
       "...       ...  \n",
       "389325  43546  \n",
       "389326  43546  \n",
       "389327  43546  \n",
       "389328  43546  \n",
       "389329  43546  \n",
       "389330  43546  \n",
       "389331  43546  \n",
       "389332  43546  \n",
       "389333  43546  \n",
       "389334  43546  \n",
       "389335  43546  \n",
       "389336  43546  \n",
       "389337  43546  \n",
       "389338  43546  \n",
       "389339  43546  \n",
       "389340  43546  \n",
       "389341  43546  \n",
       "389342  43546  \n",
       "389343  43546  \n",
       "389344  43546  \n",
       "389345  43546  \n",
       "389346  43546  \n",
       "389347  43546  \n",
       "389348  43546  \n",
       "389349  43546  \n",
       "389350  43546  \n",
       "389351  43546  \n",
       "389352  43546  \n",
       "389353  43546  \n",
       "389354  43546  \n",
       "\n",
       "[389355 rows x 5 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#　想对全部营养数据做一些分析，\n",
    "# 首先将各食物的营养成分列表转为dataframe\n",
    "nutrients"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>food</th>\n",
       "      <th>fgroup</th>\n",
       "      <th>id</th>\n",
       "      <th>manufacturer</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Cheese, caraway</td>\n",
       "      <td>Dairy and Egg Products</td>\n",
       "      <td>1008</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cheese, cheddar</td>\n",
       "      <td>Dairy and Egg Products</td>\n",
       "      <td>1009</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Cheese, edam</td>\n",
       "      <td>Dairy and Egg Products</td>\n",
       "      <td>1018</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Cheese, feta</td>\n",
       "      <td>Dairy and Egg Products</td>\n",
       "      <td>1019</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Cheese, mozzarella, part skim milk</td>\n",
       "      <td>Dairy and Egg Products</td>\n",
       "      <td>1028</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 food                  fgroup    id  \\\n",
       "0                     Cheese, caraway  Dairy and Egg Products  1008   \n",
       "1                     Cheese, cheddar  Dairy and Egg Products  1009   \n",
       "2                        Cheese, edam  Dairy and Egg Products  1018   \n",
       "3                        Cheese, feta  Dairy and Egg Products  1019   \n",
       "4  Cheese, mozzarella, part skim milk  Dairy and Egg Products  1028   \n",
       "\n",
       "  manufacturer  \n",
       "0               \n",
       "1               \n",
       "2               \n",
       "3               \n",
       "4               "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "col_mapping = {'description': 'food',\n",
    "               'group': 'fgroup'}\n",
    "info = info.rename(columns=col_mapping, copy=False)\n",
    "info.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "col_mapping = {'description': 'nutrient',\n",
    "               'group': 'nutgroup'}\n",
    "nutrients = nutrients.rename(columns=col_mapping, copy=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nutrient</th>\n",
       "      <th>nutgroup</th>\n",
       "      <th>units</th>\n",
       "      <th>value</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Protein</td>\n",
       "      <td>Composition</td>\n",
       "      <td>g</td>\n",
       "      <td>25.18</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Total lipid (fat)</td>\n",
       "      <td>Composition</td>\n",
       "      <td>g</td>\n",
       "      <td>29.20</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Carbohydrate, by difference</td>\n",
       "      <td>Composition</td>\n",
       "      <td>g</td>\n",
       "      <td>3.06</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ash</td>\n",
       "      <td>Other</td>\n",
       "      <td>g</td>\n",
       "      <td>3.28</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Energy</td>\n",
       "      <td>Energy</td>\n",
       "      <td>kcal</td>\n",
       "      <td>376.00</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      nutrient     nutgroup units   value    id\n",
       "0                      Protein  Composition     g   25.18  1008\n",
       "1            Total lipid (fat)  Composition     g   29.20  1008\n",
       "2  Carbohydrate, by difference  Composition     g    3.06  1008\n",
       "3                          Ash        Other     g    3.28  1008\n",
       "4                       Energy       Energy  kcal  376.00  1008"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nutrients.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 389355 entries, 0 to 389354\n",
      "Data columns (total 5 columns):\n",
      "nutrient    389355 non-null object\n",
      "nutgroup    389355 non-null object\n",
      "units       389355 non-null object\n",
      "value       389355 non-null float64\n",
      "id          389355 non-null int64\n",
      "dtypes: float64(1), int64(1), object(3)\n",
      "memory usage: 14.9+ MB\n"
     ]
    }
   ],
   "source": [
    "nutrients.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6636 entries, 0 to 6635\n",
      "Data columns (total 4 columns):\n",
      "food            6636 non-null object\n",
      "fgroup          6636 non-null object\n",
      "id              6636 non-null int64\n",
      "manufacturer    5195 non-null object\n",
      "dtypes: int64(1), object(3)\n",
      "memory usage: 207.5+ KB\n"
     ]
    }
   ],
   "source": [
    "info.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14179"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nutrients.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "nutrients = nutrients.drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nutrient</th>\n",
       "      <th>nutgroup</th>\n",
       "      <th>units</th>\n",
       "      <th>value</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Protein</td>\n",
       "      <td>Composition</td>\n",
       "      <td>g</td>\n",
       "      <td>25.180</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Total lipid (fat)</td>\n",
       "      <td>Composition</td>\n",
       "      <td>g</td>\n",
       "      <td>29.200</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Carbohydrate, by difference</td>\n",
       "      <td>Composition</td>\n",
       "      <td>g</td>\n",
       "      <td>3.060</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ash</td>\n",
       "      <td>Other</td>\n",
       "      <td>g</td>\n",
       "      <td>3.280</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Energy</td>\n",
       "      <td>Energy</td>\n",
       "      <td>kcal</td>\n",
       "      <td>376.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Water</td>\n",
       "      <td>Composition</td>\n",
       "      <td>g</td>\n",
       "      <td>39.280</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Energy</td>\n",
       "      <td>Energy</td>\n",
       "      <td>kJ</td>\n",
       "      <td>1573.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Fiber, total dietary</td>\n",
       "      <td>Composition</td>\n",
       "      <td>g</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Calcium, Ca</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mg</td>\n",
       "      <td>673.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Iron, Fe</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.640</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Magnesium, Mg</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mg</td>\n",
       "      <td>22.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Phosphorus, P</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mg</td>\n",
       "      <td>490.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Potassium, K</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mg</td>\n",
       "      <td>93.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Sodium, Na</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mg</td>\n",
       "      <td>690.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Zinc, Zn</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mg</td>\n",
       "      <td>2.940</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Copper, Cu</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.024</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Manganese, Mn</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.021</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Selenium, Se</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mcg</td>\n",
       "      <td>14.500</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Vitamin A, IU</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>IU</td>\n",
       "      <td>1054.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Retinol</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>262.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Vitamin A, RAE</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg_RAE</td>\n",
       "      <td>271.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Vitamin C, total ascorbic acid</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Thiamin</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.031</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Riboflavin</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.450</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Niacin</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.180</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Pantothenic acid</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.190</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Vitamin B-6</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.074</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Folate, total</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>18.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Vitamin B-12</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>0.270</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Folic acid</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389325</th>\n",
       "      <td>Selenium, Se</td>\n",
       "      <td>Elements</td>\n",
       "      <td>mcg</td>\n",
       "      <td>1.100</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389326</th>\n",
       "      <td>Vitamin A, IU</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>IU</td>\n",
       "      <td>5.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389327</th>\n",
       "      <td>Retinol</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389328</th>\n",
       "      <td>Vitamin A, RAE</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg_RAE</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389329</th>\n",
       "      <td>Carotene, beta</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>2.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389330</th>\n",
       "      <td>Carotene, alpha</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>2.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389331</th>\n",
       "      <td>Vitamin E (alpha-tocopherol)</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.250</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389332</th>\n",
       "      <td>Vitamin D</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>IU</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389333</th>\n",
       "      <td>Vitamin D (D2 + D3)</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389334</th>\n",
       "      <td>Cryptoxanthin, beta</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389335</th>\n",
       "      <td>Lycopene</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389336</th>\n",
       "      <td>Lutein + zeaxanthin</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>20.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389337</th>\n",
       "      <td>Vitamin C, total ascorbic acid</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>21.900</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389338</th>\n",
       "      <td>Thiamin</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.020</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389339</th>\n",
       "      <td>Riboflavin</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.060</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389340</th>\n",
       "      <td>Niacin</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.540</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389341</th>\n",
       "      <td>Vitamin B-6</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.260</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389342</th>\n",
       "      <td>Folate, total</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>17.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389343</th>\n",
       "      <td>Vitamin B-12</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389344</th>\n",
       "      <td>Choline, total</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>4.100</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389345</th>\n",
       "      <td>Vitamin K (phylloquinone)</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>0.500</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389346</th>\n",
       "      <td>Folic acid</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389347</th>\n",
       "      <td>Folate, food</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>17.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389348</th>\n",
       "      <td>Folate, DFE</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg_DFE</td>\n",
       "      <td>17.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389349</th>\n",
       "      <td>Vitamin E, added</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389350</th>\n",
       "      <td>Vitamin B-12, added</td>\n",
       "      <td>Vitamins</td>\n",
       "      <td>mcg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389351</th>\n",
       "      <td>Cholesterol</td>\n",
       "      <td>Other</td>\n",
       "      <td>mg</td>\n",
       "      <td>0.000</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389352</th>\n",
       "      <td>Fatty acids, total saturated</td>\n",
       "      <td>Other</td>\n",
       "      <td>g</td>\n",
       "      <td>0.072</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389353</th>\n",
       "      <td>Fatty acids, total monounsaturated</td>\n",
       "      <td>Other</td>\n",
       "      <td>g</td>\n",
       "      <td>0.028</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389354</th>\n",
       "      <td>Fatty acids, total polyunsaturated</td>\n",
       "      <td>Other</td>\n",
       "      <td>g</td>\n",
       "      <td>0.041</td>\n",
       "      <td>43546</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>375176 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  nutrient     nutgroup    units     value  \\\n",
       "0                                  Protein  Composition        g    25.180   \n",
       "1                        Total lipid (fat)  Composition        g    29.200   \n",
       "2              Carbohydrate, by difference  Composition        g     3.060   \n",
       "3                                      Ash        Other        g     3.280   \n",
       "4                                   Energy       Energy     kcal   376.000   \n",
       "5                                    Water  Composition        g    39.280   \n",
       "6                                   Energy       Energy       kJ  1573.000   \n",
       "7                     Fiber, total dietary  Composition        g     0.000   \n",
       "8                              Calcium, Ca     Elements       mg   673.000   \n",
       "9                                 Iron, Fe     Elements       mg     0.640   \n",
       "10                           Magnesium, Mg     Elements       mg    22.000   \n",
       "11                           Phosphorus, P     Elements       mg   490.000   \n",
       "12                            Potassium, K     Elements       mg    93.000   \n",
       "13                              Sodium, Na     Elements       mg   690.000   \n",
       "14                                Zinc, Zn     Elements       mg     2.940   \n",
       "15                              Copper, Cu     Elements       mg     0.024   \n",
       "16                           Manganese, Mn     Elements       mg     0.021   \n",
       "17                            Selenium, Se     Elements      mcg    14.500   \n",
       "18                           Vitamin A, IU     Vitamins       IU  1054.000   \n",
       "19                                 Retinol     Vitamins      mcg   262.000   \n",
       "20                          Vitamin A, RAE     Vitamins  mcg_RAE   271.000   \n",
       "21          Vitamin C, total ascorbic acid     Vitamins       mg     0.000   \n",
       "22                                 Thiamin     Vitamins       mg     0.031   \n",
       "23                              Riboflavin     Vitamins       mg     0.450   \n",
       "24                                  Niacin     Vitamins       mg     0.180   \n",
       "25                        Pantothenic acid     Vitamins       mg     0.190   \n",
       "26                             Vitamin B-6     Vitamins       mg     0.074   \n",
       "27                           Folate, total     Vitamins      mcg    18.000   \n",
       "28                            Vitamin B-12     Vitamins      mcg     0.270   \n",
       "29                              Folic acid     Vitamins      mcg     0.000   \n",
       "...                                    ...          ...      ...       ...   \n",
       "389325                        Selenium, Se     Elements      mcg     1.100   \n",
       "389326                       Vitamin A, IU     Vitamins       IU     5.000   \n",
       "389327                             Retinol     Vitamins      mcg     0.000   \n",
       "389328                      Vitamin A, RAE     Vitamins  mcg_RAE     0.000   \n",
       "389329                      Carotene, beta     Vitamins      mcg     2.000   \n",
       "389330                     Carotene, alpha     Vitamins      mcg     2.000   \n",
       "389331        Vitamin E (alpha-tocopherol)     Vitamins       mg     0.250   \n",
       "389332                           Vitamin D     Vitamins       IU     0.000   \n",
       "389333                 Vitamin D (D2 + D3)     Vitamins      mcg     0.000   \n",
       "389334                 Cryptoxanthin, beta     Vitamins      mcg     0.000   \n",
       "389335                            Lycopene     Vitamins      mcg     0.000   \n",
       "389336                 Lutein + zeaxanthin     Vitamins      mcg    20.000   \n",
       "389337      Vitamin C, total ascorbic acid     Vitamins       mg    21.900   \n",
       "389338                             Thiamin     Vitamins       mg     0.020   \n",
       "389339                          Riboflavin     Vitamins       mg     0.060   \n",
       "389340                              Niacin     Vitamins       mg     0.540   \n",
       "389341                         Vitamin B-6     Vitamins       mg     0.260   \n",
       "389342                       Folate, total     Vitamins      mcg    17.000   \n",
       "389343                        Vitamin B-12     Vitamins      mcg     0.000   \n",
       "389344                      Choline, total     Vitamins       mg     4.100   \n",
       "389345           Vitamin K (phylloquinone)     Vitamins      mcg     0.500   \n",
       "389346                          Folic acid     Vitamins      mcg     0.000   \n",
       "389347                        Folate, food     Vitamins      mcg    17.000   \n",
       "389348                         Folate, DFE     Vitamins  mcg_DFE    17.000   \n",
       "389349                    Vitamin E, added     Vitamins       mg     0.000   \n",
       "389350                 Vitamin B-12, added     Vitamins      mcg     0.000   \n",
       "389351                         Cholesterol        Other       mg     0.000   \n",
       "389352        Fatty acids, total saturated        Other        g     0.072   \n",
       "389353  Fatty acids, total monounsaturated        Other        g     0.028   \n",
       "389354  Fatty acids, total polyunsaturated        Other        g     0.041   \n",
       "\n",
       "           id  \n",
       "0        1008  \n",
       "1        1008  \n",
       "2        1008  \n",
       "3        1008  \n",
       "4        1008  \n",
       "5        1008  \n",
       "6        1008  \n",
       "7        1008  \n",
       "8        1008  \n",
       "9        1008  \n",
       "10       1008  \n",
       "11       1008  \n",
       "12       1008  \n",
       "13       1008  \n",
       "14       1008  \n",
       "15       1008  \n",
       "16       1008  \n",
       "17       1008  \n",
       "18       1008  \n",
       "19       1008  \n",
       "20       1008  \n",
       "21       1008  \n",
       "22       1008  \n",
       "23       1008  \n",
       "24       1008  \n",
       "25       1008  \n",
       "26       1008  \n",
       "27       1008  \n",
       "28       1008  \n",
       "29       1008  \n",
       "...       ...  \n",
       "389325  43546  \n",
       "389326  43546  \n",
       "389327  43546  \n",
       "389328  43546  \n",
       "389329  43546  \n",
       "389330  43546  \n",
       "389331  43546  \n",
       "389332  43546  \n",
       "389333  43546  \n",
       "389334  43546  \n",
       "389335  43546  \n",
       "389336  43546  \n",
       "389337  43546  \n",
       "389338  43546  \n",
       "389339  43546  \n",
       "389340  43546  \n",
       "389341  43546  \n",
       "389342  43546  \n",
       "389343  43546  \n",
       "389344  43546  \n",
       "389345  43546  \n",
       "389346  43546  \n",
       "389347  43546  \n",
       "389348  43546  \n",
       "389349  43546  \n",
       "389350  43546  \n",
       "389351  43546  \n",
       "389352  43546  \n",
       "389353  43546  \n",
       "389354  43546  \n",
       "\n",
       "[375176 rows x 5 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nutrients"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 375176 entries, 0 to 375175\n",
      "Data columns (total 8 columns):\n",
      "nutrient        375176 non-null object\n",
      "nutgroup        375176 non-null object\n",
      "units           375176 non-null object\n",
      "value           375176 non-null float64\n",
      "id              375176 non-null int64\n",
      "food            375176 non-null object\n",
      "fgroup          375176 non-null object\n",
      "manufacturer    293054 non-null object\n",
      "dtypes: float64(1), int64(1), object(6)\n",
      "memory usage: 25.8+ MB\n"
     ]
    }
   ],
   "source": [
    "ndata = pd.merge(nutrients, info, on='id', how='outer')\n",
    "ndata.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nutrient                                       Glycine\n",
       "nutgroup                                   Amino Acids\n",
       "units                                                g\n",
       "value                                             0.04\n",
       "id                                                6158\n",
       "food            Soup, tomato bisque, canned, condensed\n",
       "fgroup                      Soups, Sauces, and Gravies\n",
       "manufacturer                                          \n",
       "Name: 30000, dtype: object"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "ndata.iloc[30000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f73336278>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f732e89e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 根据食物分类和营养类型画出一幅中位值图\n",
    "result = ndata.groupby(['nutrient', 'fgroup'])['value'].quantile(0.5)\n",
    "result['Zinc, Zn'].sort_values().plot(kind='barh')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 根据上图，按照锌含量从多到少进行排序绘图。\n",
    "by_nutrient = ndata.groupby(['nutgroup', 'nutrient'])\n",
    "get_maximum = lambda x: x.loc[x.value.idxmax()]\n",
    "get_minimum = lambda x: x.loc[x.value.idxmin()]\n",
    "\n",
    "max_foods = by_nutrient.apply(get_maximum)[['value', 'food']]\n",
    "max_foods.food = max_foods.food.str[:50]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "MultiIndex: 94 entries, (Amino Acids, Alanine) to (Vitamins, Vitamin K (phylloquinone))\n",
      "Data columns (total 2 columns):\n",
      "value    94 non-null float64\n",
      "food     94 non-null object\n",
      "dtypes: float64(1), object(1)\n",
      "memory usage: 2.6+ KB\n"
     ]
    }
   ],
   "source": [
    "max_foods.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nutrient\n",
       "Alanine                           Gelatins, dry powder, unsweetened\n",
       "Arginine                               Seeds, sesame flour, low-fat\n",
       "Aspartic acid                                   Soy protein isolate\n",
       "Cystine                Seeds, cottonseed flour, low fat (glandless)\n",
       "Glutamic acid                                   Soy protein isolate\n",
       "Glycine                           Gelatins, dry powder, unsweetened\n",
       "Histidine                Whale, beluga, meat, dried (Alaska Native)\n",
       "Hydroxyproline    KENTUCKY FRIED CHICKEN, Fried Chicken, ORIGINA...\n",
       "Isoleucine        Soy protein isolate, PROTEIN TECHNOLOGIES INTE...\n",
       "Leucine           Soy protein isolate, PROTEIN TECHNOLOGIES INTE...\n",
       "Lysine            Seal, bearded (Oogruk), meat, dried (Alaska Na...\n",
       "Methionine                    Fish, cod, Atlantic, dried and salted\n",
       "Phenylalanine     Soy protein isolate, PROTEIN TECHNOLOGIES INTE...\n",
       "Proline                           Gelatins, dry powder, unsweetened\n",
       "Serine            Soy protein isolate, PROTEIN TECHNOLOGIES INTE...\n",
       "Threonine         Soy protein isolate, PROTEIN TECHNOLOGIES INTE...\n",
       "Tryptophan         Sea lion, Steller, meat with fat (Alaska Native)\n",
       "Tyrosine          Soy protein isolate, PROTEIN TECHNOLOGIES INTE...\n",
       "Valine            Soy protein isolate, PROTEIN TECHNOLOGIES INTE...\n",
       "Name: food, dtype: object"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max_foods.loc['Amino Acids']['food']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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